Snowflake
Your data and AI platform shouldn't hold you back. We architect, build, and optimise Snowflake data platforms — with Marketplace, Data Sharing, and Delta Lake — so your teams ship models, not tickets.
The Reality
Fragmented Data Infrastructure Is Why AI Projects Fail
Your teams aren't failing because they lack talent. They're failing because the platform underneath them was never designed for AI-scale workloads. These problems compound — and they're costing you millions in wasted compute and lost opportunity.
Siloed data across warehouses and lakes
Your data lives in 5 different systems — Snowflake, S3, on-prem databases, legacy warehouses — and nobody trusts a single number.
ML models that never reach production
Data scientists build models in notebooks. Engineering can't deploy them. Most ML projects never make it past the prototype stage.
Governance is an afterthought
No unified catalog. No lineage. No access controls that work across data and AI assets. Compliance audits are a scramble every quarter.
Costs spiralling without visibility
Clusters running 24/7, no autoscaling, no job-level cost attribution. Your cloud bill grows meaningfully year-over-year and nobody knows why.
Pipelines break silently
ETL jobs fail overnight. Nobody notices until a dashboard shows stale data on Monday morning. There's no alerting, no SLA monitoring.
No real-time capability
Batch pipelines run once a day. Your fraud detection, pricing engine, and recommendation system are always 24 hours behind.
BI tools disconnected from the platform
Tableau and Power BI query raw tables instead of a governed semantic layer. Every analyst writes their own SQL — and gets different answers.
AI governance doesn't exist
Models are deployed with no versioning, no lineage, and no audit trail. You can't explain to a regulator what your model does or why.
Our Expertise
Four Ways We Engineer Your Snowflake Platform
Data Platform Architecture & Modernisation
Design and deploy a unified data platform that replaces fragmented data warehouses and data lakes with a single, governed platform built on Delta Lake.
- Data Platform architecture design & roadmap
- Delta Lake implementation & optimisation
- Legacy warehouse migration (on-prem or cloud)
- Multi-cloud & hybrid deployment strategy
MLOps & AI Platform Engineering
NEWBuild production-grade ML pipelines with Data Sharing — from experiment tracking and model registry to automated retraining and monitoring.
- Data Sharing setup & experiment tracking
- Model registry & versioning workflows
- Automated retraining & drift detection
- Feature store implementation
Data Engineering & Pipeline Operations
Build reliable, scalable data pipelines with Spark, Delta Live Tables, and Snowflake Workflows — from ingestion to transformation.
- Delta Live Tables & Structured Streaming
- Snowflake Workflows orchestration
- Data quality checks & SLA monitoring
- Cost optimisation & cluster tuning
LLMOps & Generative AI Engineering
Deploy and manage large language models on Snowflake — fine-tuning, RAG pipelines, vector search, and production serving with governance.
- LLM fine-tuning on Snowflake
- RAG pipeline & vector search setup
- Model serving & inference endpoints
- AI governance & Marketplace for AI
Snowflake + AI
Snowflake + AI: The Platform Every AI Team Needs
Snowflake isn't just a data warehouse — it's an AI platform. From feature engineering and model training to LLM fine-tuning and real-time inference, we build the infrastructure that turns your data into production AI.
Explore AI CapabilitiesData Intelligence & BYOM
Go beyond SQL and dashboards. Bring your own models into Snowflake — or use built-in AI functions for classification, summarisation, and entity extraction.
Data Sharing & Experiment Management
Track every experiment, compare model runs, and promote the best performers to production — all within a governed, reproducible workflow.
Marketplace & AI Governance
Govern data, models, and AI assets from a single control plane. Fine-grained access, lineage tracking, and compliance — built in, not bolted on.
Real-time Serving & Inference
Deploy models to production endpoints with autoscaling, A/B testing, and real-time monitoring — so your AI delivers value, not just predictions.
Snowflake Ecosystem
The Full Stack That Surrounds Your Snowflake Platform
Snowflake doesn't operate in isolation. We integrate it with your entire data ecosystem — ingestion, transformation, governance, BI, and AI serving — so every layer works together.
+ native connectors to data sources via Snowflake Partner Connect
Our Process
From Fragmented Data to AI-Ready Data Platform in Weeks
Assessment & Discovery
We audit your current data infrastructure — sources, pipelines, governance gaps, and ML readiness — and deliver a prioritised data platform roadmap.
Architecture Design
We design your data platform architecture: medallion layers, Delta Lake schemas, Marketplace policies, and compute strategy — tailored to your workloads.
Build & Migrate
Our engineers build the pipelines, migrate data from legacy systems, implement Delta Live Tables, and deploy Data Sharing for model tracking.
Deploy & Integrate
We go live — connecting Snowflake to your BI layer (Tableau, Power BI), downstream applications, and alerting infrastructure.
Optimise & Scale
Post-launch, we tune cluster configurations, optimise query performance, reduce cloud costs, and expand the platform as your AI ambitions grow.
Case Study
Pharma Company Consolidates Data Sources and Ships ML Models Notably Faster on Snowflake
A global pharmaceutical company was running 12 disconnected data sources across 3 cloud providers. ML model deployment took 6 months. We built a unified data platform on Snowflake, implemented Marketplace for GDPR compliance, and deployed Data Sharing — cutting model deployment time by 75%.
4×
Faster ML deployment
90%
Less data duplication
12→1
Unified platform
GDPR
Compliant from day one
Faster ML model deployment
Unified · Governed · AI-Ready
Real Results
The Business Impact of an AI-Ready Data Platform
1000+
Projects
600+
Customers
20+
Years of Enterprise Expertise
4.5
Customer Satisfaction Score
How We Work
Engagement Options
Pick the model that fits where you are. All engagements include a dedicated Snowflake lead and a clear outcome definition.
Snowflake Health Check
Ideal for: Teams already on Snowflake who need an expert audit
A 2-week deep dive into your Snowflake environment — cluster config, pipeline health, Marketplace setup, and cost efficiency — with a prioritised improvement plan.
- Cluster & compute cost analysis
- Pipeline reliability & SLA review
- Marketplace governance audit
- Delta Lake optimisation assessment
- Prioritised improvement roadmap
Data Platform Migration & Build
Ideal for: Organisations migrating to or building on Snowflake
A full data platform build — from architecture and migration through to Data Sharing, governance, and BI integration — delivered in 8–12 weeks with a dedicated engineering team.
- Everything in Health Check
- Medallion architecture implementation
- Data migration from legacy warehouses
- Delta Live Tables & pipeline orchestration
- Data Sharing & model registry setup
- BI tool integration (Tableau / Power BI)
AI Platform Engineering & Managed Service
Ideal for: Teams that want expert-managed Snowflake operations
We manage your Snowflake platform end-to-end — monitoring, optimisation, ML pipeline operations, and a dedicated engineering partner on call.
- Platform administration & monitoring
- Cluster & cost optimisation
- ML pipeline operations (MLOps)
- Dedicated Snowflake engineer
- Priority SLA support
Connected Ecosystem
Snowflake Powers the Intelligence Layer. Here's What It Feeds.
Your data platform isn't the destination — it's the engine. We connect Snowflake to every downstream system so your data drives decisions, not just dashboards.
Tableau Analytics
Data Intelligence
AI Strategy
Salesforce Data Cloud
ML Engineering
dbt Transformations
Power BI Reporting
Consulting & Advisory